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Hardware-in-the-loop (HIL) test benches are indispensable for the development of modern vehicle dynamics controllers (VDCs). They can be regarded as a standard methodology today, because of the extremely safety critical nature of the multi-sensor and multi-actuator systems used in vehicle dynamics control. The required high quality standards can only be ensured by systematic testing within a virtual HIL environment before going into a real car. The steering system is an important aspect of the automobile from operational safety and driver enjoyment perspectives. Current Problem/Opportunity is realistic subjective steering feel prediction before vehicle build. And upfront predict the handling characteristics more accurately with subjective feel before proto build. Current Issue is difficult to convert the objective data into subjective feel and difficult to incorporate the nonlinear steering characteristics with hysterics, friction and power assist curves using virtual simulation.

A four-wheeled automobile during braking event in which left and right wheels of the vehicle are on different mu surfaces, has high chances of experiencing spin, which may lead to stability issues on vehicle. This paper intends to provide a mathematical approach to predict the deceleration at which vehicle will spin during braking in a differential mu surface, and determine the effect of influencing parameters on the extent of the vehicle spin tendency. This paper also provides a correlation between theoretical vs actual decelerations for vehicles to exhibit vehicle spin tendency. This paper helps in providing sufficient aid/tool for system designer to predetermine the vehicle spin at early level of system designs and make necessary amendments at initial stage of prototype development rather than late changes, to create a product which gives safe driving experience.

The side door closing effort is one of the main evaluating parameters which demonstrates the build quality of the vehicle. The side door hinge axis inclination is one of the key attributes that affect the side door closing effort. Commonly, the hinge axis is inclined in two directions of a vehicle to have necessary door rise during the door opening event. Due to the process and assembly variations in the door assembly, the upper and lower hinge axis of the side door deviates from the design axis. In this paper, the deviations in the side door hinge axis and its effects on the side door closing velocity is discussed. The deviations of the side door hinge axis are studied with a coordinate measuring machine. The side door closing velocity of the vehicle is measured with the velocity meter. The study revealed that side door closing velocity is increasing with an increase in the deviation of the top and bottom door hinge axis from the design hinge axis.

Costlier engine exhaust gas treatment systems as a result of stringent emission norms and increasing awareness about industrial effects on climate have pushed the automotive industry around the globe to shift its focus from fossil fuel driven vehicles to electrically powered ones. While Battery Electric Vehicles (BEVs) have some problematic issues such as lower range, lesser energy density and higher cost owing to not fully mature battery technology, they do provide some benefits such as lower carbon footprint and simpler transmission systems. The torque and power characteristics vary greatly between IC engines and electric motors. The longitudinal dynamics of a vehicle depends greatly on the nature of its powertrain. As a result, new challenges have emerged for simulation engineers who were until very recently accustomed only to IC engine driven vehicles.

Tractor weight transfer is the most common farm-related cause of fatalities nowadays. As in India it is getting mandatory for all safety devices across all HP ranges. Considering any changes in the weight from an attachment such as Rops, PTO device, tow hook and draw bar etc. can shift the center of gravity towards the weight. center of gravity is higher on a tractor because the tractor needs to be higher in order to complete operations over crops and rough terrain. Terrains, attachments, weights, and speeds can change the tractor’s resistance to turning over. This center of gravity placement disperses the weight so that 30 percent of the tractor’s weight is on the front axle and 70 percent is on the rear axle for two-wheel drive propelled tractors and it must remain within the tractor’s stability baseline for the tractor to remain in an upright position.

This study introduces a method to examine the flow path of the lubricant inside a transmission housing of a tractor. A typical gearbox has several loads bearing elements which are in relative sliding motion to each other which causes heat to be released. The major sources of friction as well as heat are the meshing teeth between gears (sun/planet, planet/ring & power/range drive gear), thrust washers, thrust bearings and needle roller bearings. The churning of oil performs the vital function of both lubricating these sliding interfaces and cooling these sources of heat, thereby preventing failure of the gearbox. In this paper, we have applied VOF multiphase flow model and sliding meshing to simulate the fluid flow during splashed lubrication within a mating gear box. Lubrication oil dynamics and oil surface interaction with the air is modeled using VOF multiphase approach.

The tractor usage is growing in the world due to derivative of rural economy and farming process. It needed wide range of implements based on the applications of the customer. The tractor plays a major role in Agricultural and Construction applications. In a tractor, hydraulic system is act as a heart of the vehicle which controls the draft and position of the implement. Hydraulic system consists of Powertrain assembly, 3-point linkage and DC sensing assembly. The design of hydraulic powertrain assembly is challenging because the loads acting on the system varies based on the type of implement, type of crop, stage of farming and soil conditions etc., Hydraulic powertrain assembly is designed based on standards like IS 12207-2019 which regulates the test methods for the system based on the lift capacity of the tractor. In this paper, virtual simulation has been established to optimize the design and perform the test correlation.

Attaining better acoustic performance and back-pressure is a continuous research area in the design and development of passenger vehicle exhaust system. Design parameters such as tail pipe, resonator, internal pipes and baffles, muffler dimensions, number of flow reversals, perforated holes size and number etc. govern the muffler design. However, the analysis on the flow directivity from tail pipe is limited. A case study is demonstrated in this work on the development of automotive muffler with due consideration of back pressure and flow directivity from tail pipe. CFD methodology is engaged to evaluate the back pressure of different muffler configurations. The experimental and numerical results of backpressure have been validated. The numerical results are in close agreement with experimental results.

Ride is an important attribute which must be accounted in the passenger segment vehicles. Excessive H point acceleration, Steering wheel acceleration, Pitch acceleration can reduce the comfort of the driver and the passengers during high frequency and low frequency rough road events. Excessive Understeer gradient, roll gradient, roll acceleration and Sprung mass lift could affect the Vehicle driver interaction during Steady state cornering, Braking and Step steer events. The concept architecture of the vehicle plays an important role in how comfort the vehicle will be. This paper discusses how to improve SUV ride performances by keeping handling performance attributes same or better than base vehicle. Multi Objective Optimization was carried out by keeping spring, bushing and damper characteristic as the design variables to avoid new system or component development time and cost.

Connected vehicles technology is experiencing a boom across the globe. Vehicle manufacturers have started using telematics devices which leverage mobile connectivity to pool the data. Though the primary purpose of the telematics devices is location tracking, the additional vehicle information gathered through the devices can bring in much more insights about the vehicles and its working condition. Cloud computing is one of the major enabled for connected vehicles and its data-driven solutions. On the other hand, machine learning and data analytics enable a rich customer experience understanding different inferences from the available data. From a fleet owner perspective, the revenue and the maintenance costs are directly related to the usage conditions of the vehicle. Usage information like load condition could help in efficient vehicle planning, drive mode selection and proactive maintenance [1].

Mechanical control cables or Bowden cables are widely used in various applications for push-pull actions of mechanical systems. In mid-segment tractors, the linkage systems are designed along with control cables to actuate controls such as throttle, braking, transmission shift, position control, etc. due to its design flexibility. Output force and travel efficiency are two major performance parameters that depend on the routing, cable design composition, friction material, load transfer, etc. Virtual simulations can be used to predict cable performance and efficiency. There are different methodologies currently used to model the cable. These available methods can accurately predict either performance or travel efficiency. There is no method available in-house to predict both these parameters. In this paper, a new cable modeling method is proposed by authors using multi-body simulation (MBS) software MSC ADAMS.

Computer Aided Engineering (CAE) simulations are an integral part of the product development process in an automotive industry. The conventional approach involving pre-processing, solving and post-processing is highly time-consuming. Emerging digital technologies such as Machine Learning (ML) can be implemented in early stage of product development cycle to predict key performances without need of traditional CAE. Oil Canning loadcase simulates the displacement and buckling behavior of vehicle outer styling panels. A ML model trained using historical oil canning simulation results can be used to predict the maximum displacement and classify buckling locations. This enables product development team in faster decision making and reduces overall turnaround time. Oil canning FE model features such as stiffness, distance from constraints, etc., are extracted for training database of the ML model. Initially, 32 model features were extracted from the FE model.

Globally, automotive sector is moving towards improving off-road performance, durability and safety. Need of off-road performance leads to unpredictable overload to powertrain system due to unpaved roads and abuse driving conditions. Generally, shafts and gears in the transmission system are designed to meet infinite life. But, under abuse condition, it undergo overloads in both torsional and bending modes and finally, weak part in the entire system tend to fail first. This paper represents the failure analysis of one such an incident happened in output shaft under abuse test condition. Failure mode was confirmed as torsional overload using Stereo microscope and SEM. Application stress and shear strength of the shaft was calculated and found overstressing was the cause of failure. To avoid recurrence of breakage, improvement options were identified and subjected to static torsional test to quantify the improvement level.

Light weight and Robust manufacturing technologies are always needed for transformation drive in the Automotive industry for the next-generation vehicles with greater Power to weight ratio. Innovations and process developments in materials and manufacturing processes are key to this light weighting transformation. Aluminium material has been widely used for these light weighting opportunities. However, aluminum joining techniques, characterized by their poor quality and consistency are limiting this transformation. This technical paper represents one of such case, where the part is made up of Aluminium through conventional casting route which has affected the laser weld quality due to poor casting soundness. This experiment explains in detail about the importance of Casting soundness for laser weld quality, weld penetration, strength etc., and the Product consistency.

Drive cycles have been an integral part of emission tests and virtual simulations for decades. A drive cycle is a representation of running behavior of a typical vehicle, involving the drive pattern, road characteristics and traffic characteristics. Drive cycles are typically used to assess vehicle performance parameters, perform system sizing and perform accelerated testing on a test bed or a virtual test environment, hence reducing the expenses on road tests. This study is an attempt to design a relatively robust process to generate a real world drive cycle. It is based on a Six Sigma design approach which utilizes data acquired from real world road trials. It explicitly describes the process of generating a drive cycle which closely represents the real world road drive scenario. The study also focuses on validation of the process by simulation and statistical analysis.

Objective metrics for performance evaluation of ride, handling and steering are required to compare, validate and optimize dynamic behavior of vehicles. Some of these objective metrics are recommended and defined by International Organization for Standardization (ISO) and Society of Automotive Engineers (SAE), which involve data processing, statistical analysis and complex mathematical operations on acquired data through simulation or experimental testing. Due to the complexity of operations and volume of data, evaluation is often time consuming and tedious. Process automation using existing tools such as MS Excel, nCode, Siemens LMS, etc. includes several limitations and challenges, which make it cumbersome to implement. This work is about development of a centralized platform for quantification, visualization and comparison of ride, handling and steering performance metrics obtained from testing and simulation data as per relevant ISO standards.

The complexity of Urban driving conditions and the human behavior introduces undesired variabilities while establishing Fuel economy for a vehicle. These variabilities pose a great challenge while trying to determine that single figure for assessment of vehicle’s fuel efficiency on an urban driving cycle. This becomes even more challenging when two or more vehicles are simultaneously evaluated with respect to a reference vehicle. The attempt to fit a generalized linear model, between Fuel Economy as predicted variable and components of a driving cycle as predictor variables produced oxymoronic and counter-institutive results. This is primarily due to existence of multi-collinearity among the predictor variables. The context of the study is to consider the event of driving on a cycle as a random sampling experiment. The outcome of a driving cycle is summarized into a list of predictor variables or components.

Tractor roll over is the most common farm-related cause of fatalities nowadays. ROPS (Roll-Overprotective Structures) are needed to prevent serious injury and death. It creates a protective zone around the operator when a rollover occurs. In India the ROPS is getting mandatory across all HP ranges except narrow track. In the present study states the customized ROPS application for configurable design such as Automated safety zone for all homologation standards, ROPS A0-D excel calculator for selection of material at concept stage and bolt calculator for selection of size. For the above applications below aspects need to consider such as Tractor weight, Rear housing mounting, Operator seat index position (SIP), Seat reference points (SRP) and all ROPS homologation standards. This ROPS application is to reduce the timeline, manual error and ensure the reliability of the modular optimal design for various platforms and variants.

This paper deals with the study of the phenomenon of crevice corrosion of aluminium by using an example of a corrosion failure of a joint in the automobile coolant circuit. A number of joint failures were studied to understand the corrosion pattern and for various metallurgical aspects like chemistry, hardness and microstructure. The corrosion products were analyzed using Scanning Electron Microscopy (SEM) and Energy Dispersive X-Ray Spectroscopy (EDS). This analysis indicated that the corrosion products mostly contained Aluminium Oxides with other contaminants like chlorides. The studies revealed that the clamped joint of the aluminium part and rubber hose led to the formation of a crevice with the engine coolant acting as the corrosive medium. The corrosion behavior at the location was affected by environmental factors like temperature, pH and chloride contamination.

In any industry, early detection and mitigation of a failure in component is vital for feasible design changes or development iterations or saving money. So it becomes pivotal to capture the failure mode in an accelerated way. This theory poses many challenges in devising the methodology to validate the failure mode. In real world, vehicle head lamp is exposed to all possible kinds of harsh environments such as variable daily ambient, rain, dust and engine compartment temperature …etc. This brings rapid thermal stress onto headlamp resulting into warpage cracks. At vehicle level on particular model, this failure is typically observed after 20,000-25,000 kms in a span of 3-4 months of running. Any corrective action to revalidate the design change or improvement will need similar timelines in regular way to test, which is quite high in product development cycle.